Project Summary/Abstract Obesity and asthma are the two most common chronic conditions in children. Obesity is a risk factor for asthma as well as for dyspnea not associated with airflow obstruction. Reciprocally, asthma symptoms and some asthma medications may increase risk of excess weight gain. Because no effective cures exist, and because both conditions are often established before school age, early life prevention is critical. Yet our ability to identify the most promising environmental or behavioral targets for prevention has been hampered by the fact that many exposures may be difficult to measure, often overlap and interact, and rarely occur at a single point in time. Individuals may vary in their sensitivity to exposures because of genetic or other factors. Furthermore, obesity and asthma themselves are not static ? each may first emerge in early childhood, later childhood, adolescence, or adulthood; once present they may persist, remit, or worsen; and the two outcomes may interact. Sophisticated analytic approaches are needed to handle the complex natures of both longitudinal birth cohort data as well as of the questions themselves. To this end, we propose this project, which is grounded in our large Boston-area Project Viva pre-birth cohort. We recruited mothers in early pregnancy, and have followed them and their children at frequent in-person visits (after delivery and at infancy, early childhood, mid-childhood, and the nearly completed early teen visits) as well as via annual questionnaires. Building on the outcomes we have already assessed from birth through early adolescence, we now propose to characterize adiposity and cardiometabolic health measures as well as lung function and respiratory symptoms into the mid-teen years. Using state of the art statistical methods, we will address the early life environmental exposures that, singly and as mixtures, influence the separate and co-evolution of obesity, asthma and related dysfunctions. We will refine exposure measures, characterize outcome trajectories, and disentangle confounding, mediation and moderation in associations of exposures with outcomes. Finally, we will use agent based simulation models that will draw from but also go beyond the results from our own cohort, to identify optimal levers for effective intervention, incorporating multiple levels of action from physiologogy all the way up to policy. We will contribute the data, measures, and methods we refine within our cohort to the larger ECHO enterprise, as well as findings to be followed up in the large synthetic cohort with its diversity representative of children nationwide.